Stage two. The scrobble history says what was played by name; Lidarr says what is owned, and where the files are. Neither is useful for curation until the two are tied together, and the quality of that join is what decides whether the later cull can be trusted at all. The index is a wholesale rebuild of every artist, album and track Lidarr holds, including file paths and the date each file landed -- the latter for the age floor a cull will need. It is rebuilt rather than reconciled because Lidarr is the authority and a deletion there has to disappear here, not linger as a library entry with no file behind it. Every call is a GET; nothing is written back. Matching runs at the level of the distinct artist/track pair rather than the individual play, because a verdict is a property of the name pair and there are three plays for every one of them. Two tiers: a MusicBrainz recording id, which Last.fm supplies per scrobble and Lidarr exposes as ForeignRecordingId, gives an exact join; everything else falls to a normalised name comparison. There is deliberately no third tier. A near-miss guess is worse than an admitted one, since the entire purpose of the resulting number is to state how far the matching can be relied on. Normalisation folds the ways the two sides habitually disagree: case, accents, guest credits that Last.fm puts in the artist field, trailing version suffixes, ampersands, and a leading article. Punctuation needs two opposing rules and both are load-bearing -- apostrophes are deleted so "Don't" meets "Dont", while every other mark becomes a space so "AC/DC", "AC-DC" and "AC DC" meet as well. It errs towards collapsing too much: a false match makes a track look played, a missed match makes it look abandoned, and only the second one loses music. The coverage report deliberately does not lead with matched versus unmatched. Most unmatched listening is music that was never in the library and says nothing about the matcher. The figure that matters is unmatched listening by an artist the library does hold: a track that was played, sitting next to a file it should have matched. The worst fifteen are listed by play count. The schema gains its tables additively and migrates a version 1 store in place, because rebuilding a nine-year history costs several thousand API requests.
music-curator
Build a local record of what actually gets listened to, from Last.fm.
Companion to music-mirror, which keeps an MP3 copy of a lossless library for an iPod. This one answers the question that mirror cannot: which of it is worth carrying, and which of it has not been played in years.
This is stage two. It ingests the scrobble history, indexes the library from
Lidarr, and matches one to the other. There are no playlists yet, and it writes
nothing back — every Lidarr call is a GET. See "Where this is going" below.
What it does today
- Pulls the full Last.fm scrobble history into SQLite, then keeps it current.
- Tracks loved tracks separately, as the protected set for later stages.
- Indexes every artist, album and track Lidarr knows about, with file paths and the date each file landed.
- Ties the two together and reports how well it managed.
Matching
Two tiers, and no third.
| Tier | Key | Notes |
|---|---|---|
mbid |
MusicBrainz recording id | Exact. Last.fm's per-scrobble mbid against Lidarr's ForeignRecordingId |
name |
Normalised artist and title | Everything the first tier could not carry |
none |
— | Recorded as a miss, never guessed at |
The normalisation is the load-bearing part, because the two sides disagree in
predictable ways. It folds case and accents, drops guest credits (Yellowcard feat. Tay Jardine against a tag of Yellowcard), strips a trailing
version suffix ((Remastered 2011), - Live), expands &, and removes a
leading The. Punctuation gets two different rules that pull against each
other and are both required: apostrophes are deleted, so Don't meets
Dont, while every other mark becomes a space, so AC/DC, AC-DC and
AC DC all meet as well.
It leans towards collapsing too much. A false match makes something look played; a missed match makes something look abandoned. Only one of those deletes music.
Reading the coverage report
Matched against unmatched is the wrong comparison — most unmatched listening is music that was never in the library, which says nothing at all about the matcher. The line to watch is:
unmatched by an artist the library holds: N pairs, M plays
That is a track that was played, sitting beside a file it should have matched. Those are the matcher's real misses, and every one is a candidate for being wrongly called cold in stage four. The report lists the worst fifteen by play count so they can be eyeballed.
How the ingest works
Two halves, both taking their bounds from the database rather than from a saved cursor, so an interrupted run resumes from what it actually has.
| Half | Window | Purpose |
|---|---|---|
| Catch-up | newest held → now |
New scrobbles since the last pass |
| Backfill | start → oldest held |
Walks towards the beginning of the history |
The backfill asks repeatedly for the newest page of everything at or before a cursor, and moves the cursor to the oldest scrobble that came back. When a whole page shares a single second the cursor cannot move without stepping over the rest of that second, so it takes the next page of the same window instead.
Both windows are bounded at both ends, so paging cannot shift under the fetch while new scrobbles arrive mid-run.
Three details of the API that are easy to get wrong, all handled:
- The currently-playing track is prepended to the first page with no timestamp at all. Stored once, it would come back on every pass forever.
- A lone result is returned as a bare object, not a one-item list.
- MBIDs are empty strings rather than absent when unknown, and an empty string looks like a usable join key right up until it silently matches everything.
Scrobbles have no identifier, so the primary key is timestamp plus artist plus track. Two plays of the same track in the same second collapse into one; they are genuinely indistinguishable, and a surrogate key would make re-ingest non-idempotent, which is a far worse trade.
Retries cover error 29 (rate limit) and the backend failures, 8, 11 and 16, with an exponential backoff. An invalid or suspended key fails immediately rather than retrying four more times to reach the same conclusion.
Usage
music-curator # one pass, then report
music-curator --interval 6h # keep running
music-curator --report-only # report on the store, fetch nothing
| Option | Environment variable | Default | Meaning |
|---|---|---|---|
--user |
MUSIC_CURATOR_LASTFM_USER |
— | Last.fm username to read |
--api-key |
MUSIC_CURATOR_LASTFM_API_KEY |
— | Last.fm API key |
--db |
MUSIC_CURATOR_DB |
/data/curator.db |
Path to the SQLite store |
--interval |
MUSIC_CURATOR_INTERVAL |
unset | Repeat forever, e.g. 45m, 6h, 1d |
--request-delay |
MUSIC_CURATOR_REQUEST_DELAY |
0.25 |
Seconds between API requests |
--backfill-limit |
MUSIC_CURATOR_BACKFILL_LIMIT |
0 |
Cap backfill requests per pass; 0 for no cap |
--lidarr-url |
MUSIC_CURATOR_LIDARR_URL |
unset | Lidarr base URL, e.g. http://lidarr:8686 |
--lidarr-api-key |
MUSIC_CURATOR_LIDARR_API_KEY |
unset | Lidarr API key |
--skip-index |
— | off | Match against the index already held |
--report-only |
— | off | Report without fetching |
A Last.fm API key is all that is needed. None of the endpoints used here authenticate a user, so there is no shared secret, no session key and no signing.
The first pass over a long history is thousands of requests at 200 scrobbles
each. --backfill-limit spreads that over several passes if you would rather
not do it in one.
Running it on TrueNAS Scale
compose.yaml is a Custom App definition. Adjust the host path and the user:
to match your pool, set the API key through the TrueNAS UI rather than in the
file, then add it as a custom app. The image is published to this Gitea's
registry on every release:
code.emmathe.dev/lyrathorpe/music-curator:latest
Give the store its own dataset. It is derived data and can be rebuilt from Last.fm, but rebuilding means downloading the whole history again.
Tests
docker build --target test . # what CI runs
pytest # needs pytest on PATH
The suite runs against fake transports for both services. The Last.fm one
reproduces its paging, its from/to semantics and its awkward response
shapes; the Lidarr one serves a canned library split across the same four
endpoints the indexer calls, so the stitching is exercised rather than
stubbed. No network, no credentials, no rate limit. On a Nix machine:
nix shell nixpkgs#python3Packages.pytest -c pytest
Where this is going
| Stage | Status |
|---|---|
| Last.fm ingest and store | done |
| Lidarr index and the scrobble-to-track matcher | done |
| M3U playlists written into the mirror | next |
| Cold-music report, unmonitoring what is not played | last |
The cull will unmonitor cold albums in Lidarr and tag their artists. It will
never delete files: Lidarr's AlbumResource has no tags at all, so tagging
only works per artist, and an artist is only tagged when every one of their
albums qualifies. It will also refuse to run at all if the matcher's coverage
is poor, because an unmatched track is not an unplayed track.